Possession plot for basketball

unc_miami_poss_plot.R

# use bigballR to fetch schedule 
schedule <-
  bigballR::get_team_schedule(season = "2023-24", team.name = "North Carolina")

# grab miami home game pbp
unc_miami_pbp <- bigballR::get_play_by_play(schedule$Game_ID[28])

# add index to determine first half and second half 
um_index <- which(unc_miami_pbp$Half_Status == 2)[1]

# denote when the half changes 
# could also maybe do this smarter? 
# divide up by every 10/20 possessions? 
first_half_poss <- unc_miami_pbp$Poss_Num[um_index] / 2

# manipulate the data for a viz
canes_heels <- unc_miami_pbp |>
  dplyr::mutate(
    scoring = dplyr::case_match(Event_Result,
                                "made" ~ TRUE,
                                "missed" ~ FALSE,
                                NA ~ FALSE),
    pts_value = dplyr::case_when(
      Event_Type == "Turnover" ~ -1,
      Event_Result == "missed" & Shot_Value %in% c(1, 2, 3) ~ 0,
      Event_Result == "made" & Shot_Value == 1 ~ 1,
      Event_Result == "made" & Shot_Value == 2 ~ 2,
      Event_Result == "made" & Shot_Value == 3 ~ 3,
      .default = 0
    ),
    pts_shape = dplyr::case_match(pts_value,
                                  -1 ~ 4,
                                  0 ~ 48,
                                  1 ~ 49,
                                  2 ~ 50,
                                  3 ~ 51)
  )

# make the plot using geom_point with different shapes
# could productionize this into a function for _any_ game
# in order to do that, would need to determine points per trip
# and any annotations separately 
canes_heels_plot <- canes_heels |>
  ggplot2::ggplot(ggplot2::aes(
    x = Poss_Num / 2,
    y = Poss_Team,
    color = scoring,
    size = pts_value / 2
  )) +
  ggplot2::geom_point(ggplot2::aes(shape = factor(pts_shape)),
                      position = ggplot2::position_dodge(width = 0.5)) +
  ggplot2::scale_color_manual(values = c("red", "darkgreen")) +
  ggplot2::scale_shape_manual(values = c(4, 45, 49, 50, 51)) +
  ggplot2::scale_x_continuous(breaks = seq(0, 75, 5), limits = c(0, 75)) +
  ggplot2::geom_vline(xintercept = first_half_poss,
                      linetype = "dashed",
                      color = "#333333") +
  ggplot2::annotate(
    "rect",
    fill = "yellow",
    alpha = 0.1,
    xmin = 126.5 / 2,
    xmax = 144.5 / 2,
    ymin = -Inf,
    ymax = Inf
  ) +
  ggthemes::theme_fivethirtyeight() +
  ggplot2::theme(
    legend.position = "none",
    axis.text.y = cbbplotR::element_cbb_teams(size = 0.9),
    panel.grid.major = ggplot2::element_blank(),
    panel.grid.minor = ggplot2::element_blank(),
    panel.background = ggplot2::element_blank()
  ) +
  ggplot2::labs(
    x = "Possessions",
    y = "",
    title = "North Carolina 75, Miami 71",
    subtitle = "Green represents a scoring possession: three-pointers, two-pointers, free throws  \nRed represents empty possessions: missed shots (-) or turnovers (x)",
    caption = "Bless your chart | February 26, 2024 | data via bigballR + cbbplotR"
  ) +
  ggplot2::annotate(
    "label",
    x = 10 / 2,
    y = 1.5,
    label = "Points per trip \nNorth Carolina 1.01 \nMiami 0.96",
    size = 3,
    color = "#333333",
    fill = "floralwhite",
    fontface = "bold"
  ) +
  ggplot2::annotate(
    "label",
    x = 135 / 2,
    y = 1.5,
    label = "UNC: 0 made field goals  \nlast 4:17 of game",
    size = 2.5,
    color = "#333333",
    fill = "floralwhite",
    fontface = "bold"
  ) +
  ggplot2::annotate(
    "label",
    x = first_poss_num,
    y = 2.55,
    label = "Halftime",
    size = 2.5,
    color = "#333333",
    fill = "floralwhite",
    fontface = "bold"
  )

# save the plot 
ggplot2::ggsave(
  "unc_miami_poss_plot.png",
  canes_heels_plot,
  w = 10,
  h = 6,
  dpi = 600,
  type = 'cairo'
)